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李 琼,姚 遥,杨青春,等.基于MATLAB图像处理的大豆颗粒检测方法研究[J].中国农学通报,2018,34(30):20-25.,et al.Soybean Grain Detection Method Based on MATLAB Image Processing[J].Chinese Agricultural Science Bulletin,2018,34(30):20-25
基于MATLAB图像处理的大豆颗粒检测方法研究
Soybean Grain Detection Method Based on MATLAB Image Processing
投稿时间:2017-10-05  修订日期:2017-12-15
DOI:10.11924/j.issn.1000-6850.casb17100005
中文关键词: 计算机视觉图像处理  大豆颗粒计数  大豆颗粒大小  百粒重  MATLAB
英文关键词: computer vision image processing  soybean particle counting  soybean particle size  100 grain weight  MATLAB
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基金项目:国家重点研发计划“黄淮海大豆新品种配套栽培技术研制及试验示范”(2017YFD0101406);河南省科技攻关项目“基于移动智能终端的多 旋翼植保机飞行控制系统研究与开发”(162102210312)。
作者单位E-mail
李 琼 周口市农业科学院经济作物研究所 15290067998@163.com 
姚 遥 周口师范学院物理与电信工程学院 45988514@qq.com 
杨青春 周口市农业科学院经济作物研究所 zkyqc@qq.com 
舒文涛 周口市农业科学院经济作物研究所 shuwentao2004@126.com 
李金花 周口市农业科学院经济作物研究所 lijinhua602@163.com 
张保亮 周口市农业科学院经济作物研究所 zkzbl@126.com 
张东辉 周口市农业科学院经济作物研究所 hnzkzdh@163.com 
耿 臻 周口市农业科学院经济作物研究所 gengzhen0616@163.com 
中文摘要:
      为解决大豆单株考种过程中人力计数准确率低和数粒仪等光电方法耗时长等问题,采用计算机视觉系统及MATLAB软件开发平台代替人工大豆单株考种进行自动检测的方法。该算法采用对大豆颗粒图像进行空间滤波去除噪声及“Otsu”方法对图像进行最佳全局阈值分割处理,在对图像处理的基础上完成对大豆颗粒个数、颗粒大小两项指标的测定。以六个大豆品种周黑豆、周青豆、周豆11、周豆18、周豆22和周豆23的籽粒为试验对象,探究大豆颗粒计数、大豆颗粒大小分级两项指标的确定。实验结果表明:该算法及程序准确有效,能准确计算大豆单株颗粒个数;该算法及程序判断出的各品种大豆颗粒平均面积大小与百粒重成正相关,且决定系数为0.9141,即可得该算法及程序可准确有效的判断大豆颗粒大小。总之,基于MTALAB图像处理大豆单株颗粒检测方法的研究可相对减轻人力劳动强度及人类视觉的不足,在提高工作效率和准确度等方面有重要意义。
英文摘要:
      To solve the problems of low accuracy of human counting and time consuming of photoelectric counting and so on in laboratory test of single soybean plant, the computer vision system and the MATLAB software development platform were used in single plant test instead of human counting in laboratory test of single soybean plant. The algorithm used the spatial filtering of the soybean grain image to remove the noise, and the "Otsu" method optimized the global threshold segmentation of the image. Based on the image processing, the two factors, the number of grain and the size of grain, were measured. Two indexes, soybean grain counting and soybean grain size grading, were studied with six soybean varieties as materials, namely ‘Zhouhei soybean’,‘Zhouqing soybean’,‘Zhoudou 11’,‘Zhoudou 18’,‘Zhoudou 22’and‘Zhoudou 23’. The experimental results showed that the algorithm and the procedure were accurate and effective, and the grain number of single soybean could be calculated accurately. The algorithm and procedure determined that the average area of the soybean grain in each variety was positively correlated with the 100 grain weight, and the coefficient of determination was 0.987. So the algorithm and procedure can determine the size of soybean grain accurately and effectively. In short, the method of soybean grain detection based on MATLAB image processing can reduce the human labor intensity and human visual deficiencies relatively, and it is of certain significance in improving work efficiency and accuracy.
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